3 ms·
An excerpt of key points on forecasting from end of the article: "How to be a superforecaster: Some participants in the Good Judgment Project were given advic
by danboarder 12y ago
An excerpt of key points on forecasting from end of the article:
"How to be a superforecaster:
Some participants in the Good Judgment Project were given advice on how to transform their knowledge about the world into a probabilistic forecast – and this training, while brief, led to a sharp improvement in forecasting performance. The advice, a few pages in total, was summarised with the acronym CHAMP:
● Comparisons are important: use relevant comparisons as a starting point;
● Historical trends can help: look at history unless you have a strong reason to expect change;
● Average opinions: experts disagree, so find out what they think and pick a midpoint;
● Mathematical models: when model-based predictions are available, you should take them into account;
● Predictable biases exist and can be allowed for. Don’t let your hopes influence your forecasts, for example; don’t stubbornly cling to old forecasts in the face of news."
As a participant in the Good Judgement Project I recall this training (basically an interactive Powerpoint). I would agree that it was helpful in my forecasting performance last year.
- hywel 12y agoIt's an interesting article, but those conclusions seem so weak to me; little more than formalised common sense. Maybe the training you had did a better job of making them tangible.
- danboarder 12y agoI think you nailed it, it's formalized common sense (the article hints at this conclusion too). However, the unique addition of a way to track and improve forecasting performance over time is what makes this project work. This was accomplished through a few attempts at custom software in the last few years, and for this year they are using Inkling Markets, so far it is best platform I've experienced for tracking and improving prediction performance.